R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> x <- array(list(377
+ ,6.4
+ ,370
+ ,7.7
+ ,358
+ ,9.2
+ ,357
+ ,8.6
+ ,349
+ ,7.4
+ ,348
+ ,8.6
+ ,369
+ ,6.2
+ ,381
+ ,6
+ ,368
+ ,6.6
+ ,361
+ ,5.1
+ ,351
+ ,4.7
+ ,351
+ ,5
+ ,358
+ ,3.6
+ ,354
+ ,1.9
+ ,347
+ ,-0.1
+ ,345
+ ,-5.7
+ ,343
+ ,-5.6
+ ,340
+ ,-6.4
+ ,362
+ ,-7.7
+ ,370
+ ,-8
+ ,373
+ ,-11.9
+ ,371
+ ,-15.4
+ ,354
+ ,-15.5
+ ,357
+ ,-13.4
+ ,363
+ ,-10.9
+ ,364
+ ,-10.8
+ ,363
+ ,-7.3
+ ,358
+ ,-6.5
+ ,357
+ ,-5.1
+ ,357
+ ,-5.3
+ ,380
+ ,-6.8
+ ,378
+ ,-8.4
+ ,376
+ ,-8.4
+ ,380
+ ,-9.7
+ ,379
+ ,-8.8
+ ,384
+ ,-9.6
+ ,392
+ ,-11.5
+ ,394
+ ,-11
+ ,392
+ ,-14.9
+ ,396
+ ,-16.2
+ ,392
+ ,-14.4
+ ,396
+ ,-17.3
+ ,419
+ ,-15.7
+ ,421
+ ,-12.6
+ ,420
+ ,-9.4
+ ,418
+ ,-8.1
+ ,410
+ ,-5.4
+ ,418
+ ,-4.6
+ ,426
+ ,-4.9
+ ,428
+ ,-4
+ ,430
+ ,-3.1
+ ,424
+ ,-1.3
+ ,423
+ ,0
+ ,427
+ ,-0.4
+ ,441
+ ,3
+ ,449
+ ,0.4
+ ,452
+ ,1.2
+ ,462
+ ,0.6
+ ,455
+ ,-1.3
+ ,461
+ ,-3.2
+ ,461
+ ,-1.8
+ ,463
+ ,-3.6
+ ,462
+ ,-4.2
+ ,456
+ ,-6.9
+ ,455
+ ,-8
+ ,456
+ ,-7.5
+ ,472
+ ,-8.2
+ ,472
+ ,-7.6
+ ,471
+ ,-3.7
+ ,465
+ ,-1.7
+ ,459
+ ,-0.7
+ ,465
+ ,0.2
+ ,468
+ ,0.6
+ ,467
+ ,2.2
+ ,463
+ ,3.3
+ ,460
+ ,5.3
+ ,462
+ ,5.5
+ ,461
+ ,6.3
+ ,476
+ ,7.7
+ ,476
+ ,6.5
+ ,471
+ ,5.5
+ ,453
+ ,6.9
+ ,443
+ ,5.7
+ ,442
+ ,6.9
+ ,444
+ ,6.1
+ ,438
+ ,4.8
+ ,427
+ ,3.7
+ ,424
+ ,5.8
+ ,416
+ ,6.8
+ ,406
+ ,8.5
+ ,431
+ ,7.2
+ ,434
+ ,5
+ ,418
+ ,4.7
+ ,412
+ ,2.3
+ ,404
+ ,2.4
+ ,409
+ ,0.1
+ ,412
+ ,1.9
+ ,406
+ ,1.7
+ ,398
+ ,2
+ ,397
+ ,-1.9
+ ,385
+ ,0.5
+ ,390
+ ,-1.3
+ ,413
+ ,-3.3
+ ,413
+ ,-2.8
+ ,401
+ ,-8
+ ,397
+ ,-13.9
+ ,397
+ ,-21.9
+ ,409
+ ,-28.8
+ ,419
+ ,-27.6
+ ,424
+ ,-31.4
+ ,428
+ ,-31.8
+ ,430
+ ,-29.4
+ ,424
+ ,-27.6
+ ,433
+ ,-23.6
+ ,456
+ ,-22.8
+ ,459
+ ,-18.2
+ ,446
+ ,-17.8
+ ,441
+ ,-14.2
+ ,439
+ ,-8.8
+ ,454
+ ,-7.9
+ ,460
+ ,-7
+ ,457
+ ,-7
+ ,451
+ ,-3.6
+ ,444
+ ,-2.4
+ ,437
+ ,-4.9
+ ,443
+ ,-7.7
+ ,471
+ ,-6.5
+ ,469
+ ,-5.1
+ ,454
+ ,-3.4
+ ,444
+ ,-2.8
+ ,436
+ ,0.8)
+ ,dim=c(2
+ ,131)
+ ,dimnames=list(c('Werkloosheid'
+ ,'Conjunctuur')
+ ,1:131))
> y <- array(NA,dim=c(2,131),dimnames=list(c('Werkloosheid','Conjunctuur'),1:131))
> for (i in 1:dim(x)[1])
+ {
+ for (j in 1:dim(x)[2])
+ {
+ y[i,j] <- as.numeric(x[i,j])
+ }
+ }
> par3 = 'No Linear Trend'
> par2 = 'Do not include Seasonal Dummies'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> library(lattice)
> library(lmtest)
Loading required package: zoo
Attaching package: 'zoo'
The following object(s) are masked from package:base :
as.Date.numeric
> n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
> par1 <- as.numeric(par1)
> x <- t(y)
> k <- length(x[1,])
> n <- length(x[,1])
> x1 <- cbind(x[,par1], x[,1:k!=par1])
> mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
> colnames(x1) <- mycolnames #colnames(x)[par1]
> x <- x1
> if (par3 == 'First Differences'){
+ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
+ for (i in 1:n-1) {
+ for (j in 1:k) {
+ x2[i,j] <- x[i+1,j] - x[i,j]
+ }
+ }
+ x <- x2
+ }
> if (par2 == 'Include Monthly Dummies'){
+ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
+ for (i in 1:11){
+ x2[seq(i,n,12),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> if (par2 == 'Include Quarterly Dummies'){
+ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
+ for (i in 1:3){
+ x2[seq(i,n,4),i] <- 1
+ }
+ x <- cbind(x, x2)
+ }
> k <- length(x[1,])
> if (par3 == 'Linear Trend'){
+ x <- cbind(x, c(1:n))
+ colnames(x)[k+1] <- 't'
+ }
> x
Werkloosheid Conjunctuur
1 377 6.4
2 370 7.7
3 358 9.2
4 357 8.6
5 349 7.4
6 348 8.6
7 369 6.2
8 381 6.0
9 368 6.6
10 361 5.1
11 351 4.7
12 351 5.0
13 358 3.6
14 354 1.9
15 347 -0.1
16 345 -5.7
17 343 -5.6
18 340 -6.4
19 362 -7.7
20 370 -8.0
21 373 -11.9
22 371 -15.4
23 354 -15.5
24 357 -13.4
25 363 -10.9
26 364 -10.8
27 363 -7.3
28 358 -6.5
29 357 -5.1
30 357 -5.3
31 380 -6.8
32 378 -8.4
33 376 -8.4
34 380 -9.7
35 379 -8.8
36 384 -9.6
37 392 -11.5
38 394 -11.0
39 392 -14.9
40 396 -16.2
41 392 -14.4
42 396 -17.3
43 419 -15.7
44 421 -12.6
45 420 -9.4
46 418 -8.1
47 410 -5.4
48 418 -4.6
49 426 -4.9
50 428 -4.0
51 430 -3.1
52 424 -1.3
53 423 0.0
54 427 -0.4
55 441 3.0
56 449 0.4
57 452 1.2
58 462 0.6
59 455 -1.3
60 461 -3.2
61 461 -1.8
62 463 -3.6
63 462 -4.2
64 456 -6.9
65 455 -8.0
66 456 -7.5
67 472 -8.2
68 472 -7.6
69 471 -3.7
70 465 -1.7
71 459 -0.7
72 465 0.2
73 468 0.6
74 467 2.2
75 463 3.3
76 460 5.3
77 462 5.5
78 461 6.3
79 476 7.7
80 476 6.5
81 471 5.5
82 453 6.9
83 443 5.7
84 442 6.9
85 444 6.1
86 438 4.8
87 427 3.7
88 424 5.8
89 416 6.8
90 406 8.5
91 431 7.2
92 434 5.0
93 418 4.7
94 412 2.3
95 404 2.4
96 409 0.1
97 412 1.9
98 406 1.7
99 398 2.0
100 397 -1.9
101 385 0.5
102 390 -1.3
103 413 -3.3
104 413 -2.8
105 401 -8.0
106 397 -13.9
107 397 -21.9
108 409 -28.8
109 419 -27.6
110 424 -31.4
111 428 -31.8
112 430 -29.4
113 424 -27.6
114 433 -23.6
115 456 -22.8
116 459 -18.2
117 446 -17.8
118 441 -14.2
119 439 -8.8
120 454 -7.9
121 460 -7.0
122 457 -7.0
123 451 -3.6
124 444 -2.4
125 437 -4.9
126 443 -7.7
127 471 -6.5
128 469 -5.1
129 454 -3.4
130 444 -2.8
131 436 0.8
> k <- length(x[1,])
> df <- as.data.frame(x)
> (mylm <- lm(df))
Call:
lm(formula = df)
Coefficients:
(Intercept) Conjunctuur
415.55956 0.07012
> (mysum <- summary(mylm))
Call:
lm(formula = df)
Residuals:
Min 1Q Median 3Q Max
-75.111 -35.032 5.376 36.656 59.985
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 415.55956 3.82981 108.507 <2e-16 ***
Conjunctuur 0.07012 0.37340 0.188 0.851
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 39.62 on 129 degrees of freedom
Multiple R-squared: 0.0002733, Adjusted R-squared: -0.007477
F-statistic: 0.03526 on 1 and 129 DF, p-value: 0.8513
> if (n > n25) {
+ kp3 <- k + 3
+ nmkm3 <- n - k - 3
+ gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
+ numgqtests <- 0
+ numsignificant1 <- 0
+ numsignificant5 <- 0
+ numsignificant10 <- 0
+ for (mypoint in kp3:nmkm3) {
+ j <- 0
+ numgqtests <- numgqtests + 1
+ for (myalt in c('greater', 'two.sided', 'less')) {
+ j <- j + 1
+ gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
+ }
+ if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
+ if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
+ }
+ gqarr
+ }
[,1] [,2] [,3]
[1,] 2.842302e-02 5.684604e-02 9.715770e-01
[2,] 9.900379e-03 1.980076e-02 9.900996e-01
[3,] 2.408108e-03 4.816215e-03 9.975919e-01
[4,] 7.403563e-04 1.480713e-03 9.992596e-01
[5,] 1.718085e-04 3.436169e-04 9.998282e-01
[6,] 1.842106e-04 3.684213e-04 9.998158e-01
[7,] 3.109595e-04 6.219189e-04 9.996890e-01
[8,] 2.159583e-04 4.319167e-04 9.997840e-01
[9,] 8.476477e-05 1.695295e-04 9.999152e-01
[10,] 3.708790e-05 7.417579e-05 9.999629e-01
[11,] 1.934052e-05 3.868103e-05 9.999807e-01
[12,] 7.570615e-06 1.514123e-05 9.999924e-01
[13,] 3.152777e-06 6.305555e-06 9.999968e-01
[14,] 1.432384e-06 2.864768e-06 9.999986e-01
[15,] 2.251646e-06 4.503292e-06 9.999977e-01
[16,] 4.566081e-06 9.132163e-06 9.999954e-01
[17,] 7.132581e-06 1.426516e-05 9.999929e-01
[18,] 5.373752e-06 1.074750e-05 9.999946e-01
[19,] 2.915465e-06 5.830930e-06 9.999971e-01
[20,] 1.528674e-06 3.057348e-06 9.999985e-01
[21,] 8.466791e-07 1.693358e-06 9.999992e-01
[22,] 4.903255e-07 9.806511e-07 9.999995e-01
[23,] 3.008433e-07 6.016866e-07 9.999997e-01
[24,] 2.072906e-07 4.145812e-07 9.999998e-01
[25,] 1.646009e-07 3.292017e-07 9.999998e-01
[26,] 1.453022e-07 2.906044e-07 9.999999e-01
[27,] 3.884569e-07 7.769137e-07 9.999996e-01
[28,] 6.843687e-07 1.368737e-06 9.999993e-01
[29,] 9.652006e-07 1.930401e-06 9.999990e-01
[30,] 1.699894e-06 3.399788e-06 9.999983e-01
[31,] 2.711209e-06 5.422418e-06 9.999973e-01
[32,] 5.706486e-06 1.141297e-05 9.999943e-01
[33,] 1.853992e-05 3.707985e-05 9.999815e-01
[34,] 5.473295e-05 1.094659e-04 9.999453e-01
[35,] 9.119825e-05 1.823965e-04 9.999088e-01
[36,] 1.536738e-04 3.073476e-04 9.998463e-01
[37,] 2.142398e-04 4.284797e-04 9.997858e-01
[38,] 2.826888e-04 5.653777e-04 9.997173e-01
[39,] 1.492307e-03 2.984615e-03 9.985077e-01
[40,] 6.317428e-03 1.263486e-02 9.936826e-01
[41,] 1.963332e-02 3.926664e-02 9.803667e-01
[42,] 4.318721e-02 8.637442e-02 9.568128e-01
[43,] 7.075526e-02 1.415105e-01 9.292447e-01
[44,] 1.275032e-01 2.550063e-01 8.724968e-01
[45,] 2.263395e-01 4.526789e-01 7.736605e-01
[46,] 3.501905e-01 7.003810e-01 6.498095e-01
[47,] 4.842092e-01 9.684185e-01 5.157908e-01
[48,] 5.821188e-01 8.357624e-01 4.178812e-01
[49,] 6.642160e-01 6.715680e-01 3.357840e-01
[50,] 7.369277e-01 5.261446e-01 2.630723e-01
[51,] 8.389903e-01 3.220193e-01 1.610097e-01
[52,] 9.107244e-01 1.785513e-01 8.927564e-02
[53,] 9.527950e-01 9.440993e-02 4.720496e-02
[54,] 9.805740e-01 3.885193e-02 1.942596e-02
[55,] 9.891282e-01 2.174352e-02 1.087176e-02
[56,] 9.946371e-01 1.072584e-02 5.362920e-03
[57,] 9.972172e-01 5.565556e-03 2.782778e-03
[58,] 9.985685e-01 2.863082e-03 1.431541e-03
[59,] 9.991914e-01 1.617239e-03 8.086193e-04
[60,] 9.994045e-01 1.191076e-03 5.955379e-04
[61,] 9.995250e-01 9.499665e-04 4.749833e-04
[62,] 9.996179e-01 7.641307e-04 3.820654e-04
[63,] 9.998286e-01 3.427928e-04 1.713964e-04
[64,] 9.999218e-01 1.563233e-04 7.816167e-05
[65,] 9.999624e-01 7.514119e-05 3.757059e-05
[66,] 9.999757e-01 4.857839e-05 2.428920e-05
[67,] 9.999795e-01 4.101513e-05 2.050757e-05
[68,] 9.999859e-01 2.814678e-05 1.407339e-05
[69,] 9.999914e-01 1.728375e-05 8.641875e-06
[70,] 9.999943e-01 1.139272e-05 5.696360e-06
[71,] 9.999954e-01 9.195697e-06 4.597848e-06
[72,] 9.999957e-01 8.642382e-06 4.321191e-06
[73,] 9.999962e-01 7.614801e-06 3.807401e-06
[74,] 9.999965e-01 7.069356e-06 3.534678e-06
[75,] 9.999985e-01 2.946284e-06 1.473142e-06
[76,] 9.999995e-01 1.059168e-06 5.295839e-07
[77,] 9.999998e-01 4.587192e-07 2.293596e-07
[78,] 9.999997e-01 5.178128e-07 2.589064e-07
[79,] 9.999996e-01 8.255365e-07 4.127682e-07
[80,] 9.999993e-01 1.329232e-06 6.646158e-07
[81,] 9.999990e-01 1.968383e-06 9.841914e-07
[82,] 9.999983e-01 3.380324e-06 1.690162e-06
[83,] 9.999966e-01 6.730647e-06 3.365323e-06
[84,] 9.999933e-01 1.337077e-05 6.685386e-06
[85,] 9.999873e-01 2.542032e-05 1.271016e-05
[86,] 9.999799e-01 4.025224e-05 2.012612e-05
[87,] 9.999630e-01 7.390612e-05 3.695306e-05
[88,] 9.999358e-01 1.284786e-04 6.423931e-05
[89,] 9.998833e-01 2.333026e-04 1.166513e-04
[90,] 9.998062e-01 3.875334e-04 1.937667e-04
[91,] 9.997325e-01 5.349358e-04 2.674679e-04
[92,] 9.996027e-01 7.945969e-04 3.972985e-04
[93,] 9.993916e-01 1.216846e-03 6.084229e-04
[94,] 9.992100e-01 1.579949e-03 7.899746e-04
[95,] 9.992624e-01 1.475209e-03 7.376044e-04
[96,] 9.994010e-01 1.197989e-03 5.989947e-04
[97,] 9.998314e-01 3.372634e-04 1.686317e-04
[98,] 9.999644e-01 7.114553e-05 3.557277e-05
[99,] 9.999702e-01 5.965158e-05 2.982579e-05
[100,] 9.999807e-01 3.868913e-05 1.934457e-05
[101,] 9.999960e-01 7.970833e-06 3.985417e-06
[102,] 9.999996e-01 7.790677e-07 3.895339e-07
[103,] 1.000000e+00 7.660342e-08 3.830171e-08
[104,] 1.000000e+00 5.919452e-08 2.959726e-08
[105,] 1.000000e+00 9.372213e-08 4.686106e-08
[106,] 9.999999e-01 2.334043e-07 1.167021e-07
[107,] 9.999997e-01 6.553361e-07 3.276681e-07
[108,] 9.999991e-01 1.711115e-06 8.555574e-07
[109,] 9.999992e-01 1.568944e-06 7.844719e-07
[110,] 9.999992e-01 1.600094e-06 8.000469e-07
[111,] 9.999973e-01 5.379793e-06 2.689897e-06
[112,] 9.999927e-01 1.456953e-05 7.284767e-06
[113,] 9.999768e-01 4.632421e-05 2.316211e-05
[114,] 9.999644e-01 7.124619e-05 3.562309e-05
[115,] 9.999676e-01 6.477337e-05 3.238669e-05
[116,] 9.998892e-01 2.215415e-04 1.107708e-04
[117,] 9.996049e-01 7.902937e-04 3.951469e-04
[118,] 9.986066e-01 2.786871e-03 1.393435e-03
[119,] 9.953610e-01 9.277958e-03 4.638979e-03
[120,] 9.853921e-01 2.921578e-02 1.460789e-02
[121,] 9.752280e-01 4.954405e-02 2.477202e-02
[122,] 9.958954e-01 8.209198e-03 4.104599e-03
> postscript(file="/var/www/html/rcomp/tmp/1xme41292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
> points(x[,1]-mysum$resid)
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/2xme41292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/3xme41292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/4pwvp1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/5pwvp1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
> qqline(mysum$resid)
> grid()
> dev.off()
null device
1
> (myerror <- as.ts(mysum$resid))
Time Series:
Start = 1
End = 131
Frequency = 1
1 2 3 4 5 6
-39.00829957 -46.09944974 -58.20462301 -59.16255370 -67.07841509 -68.16255370
7 8 9 10 11 12
-46.99427647 -34.98025337 -48.02232268 -54.91714941 -64.88910320 -64.91013785
13 14 15 16 17 18
-57.81197613 -61.69277976 -68.55254873 -70.15990186 -72.16691341 -75.11082100
19 20 21 22 23 24
-53.01967083 -44.99863617 -41.72518567 -43.47978137 -60.47276982 -57.62001240
25 26 27 28 29 30
-51.79530118 -50.80231274 -52.04771703 -57.10380945 -58.20197116 -58.18794806
31 32 33 34 35 36
-35.08277479 -36.97058997 -38.97058997 -34.87943980 -35.94254376 -30.88645135
37 38 39 40 41 42
-22.75323188 -20.78828963 -22.51483913 -18.42368896 -22.54989689 -18.34656190
43 44 45 46 47 48
4.54125328 6.32389519 5.09952554 3.00837538 -5.18093651 2.76297108
49 50 51 52 53 54
10.78400573 12.72090177 14.65779781 8.53158988 7.44043972 11.46848592
55 56 57 58 59 60
25.23009317 33.41239351 36.35630110 46.39837041 39.53158988 45.66480936
61 62 63 64 65 66
45.56664764 47.69285556 46.73492487 40.92423676 40.00136383 40.96630607
67 68 69 70 71 72
57.01538693 56.97331762 55.69986712 49.55963609 43.48952057 49.42641661
73 74 75 76 77 78
52.39837041 51.28618558 47.20905852 44.06882749 46.05480439 44.99871198
79 80 81 82 83 84
59.90055026 59.98468888 55.05480439 36.95664267 27.04078129 25.95664267
85 86 87 88 89 90
28.01273508 22.10388525 11.18101231 8.03376973 -0.03634578 -10.15554215
91 92 93 94 95 96
14.93560802 18.08986215 2.11089680 -3.72082597 -11.72783752 -6.56657184
97 98 99 100 101 102
-3.69277976 -9.67875666 -17.69979131 -18.42634081 -30.59461804 -25.46841012
103 104 105 106 107 108
-2.32817909 -2.36323685 -13.99863617 -17.58495464 -17.02403053 -4.54023349
109 110 111 112 113 114
5.37562790 10.64206685 14.67011305 16.50183582 10.37562790 19.09516584
115 116 117 118 119 120
42.03907343 44.71654207 31.68849586 26.43608001 24.05745624 38.99435227
121 122 123 124 125 126
44.93124831 41.93124831 35.69285556 28.60871695 21.78400573 27.98032917
127 128 129 130 131
55.89619055 53.79802884 38.67883246 28.63676315 20.38434730
> postscript(file="/var/www/html/rcomp/tmp/6pwvp1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> dum <- cbind(lag(myerror,k=1),myerror)
> dum
Time Series:
Start = 0
End = 131
Frequency = 1
lag(myerror, k = 1) myerror
0 -39.00829957 NA
1 -46.09944974 -39.00829957
2 -58.20462301 -46.09944974
3 -59.16255370 -58.20462301
4 -67.07841509 -59.16255370
5 -68.16255370 -67.07841509
6 -46.99427647 -68.16255370
7 -34.98025337 -46.99427647
8 -48.02232268 -34.98025337
9 -54.91714941 -48.02232268
10 -64.88910320 -54.91714941
11 -64.91013785 -64.88910320
12 -57.81197613 -64.91013785
13 -61.69277976 -57.81197613
14 -68.55254873 -61.69277976
15 -70.15990186 -68.55254873
16 -72.16691341 -70.15990186
17 -75.11082100 -72.16691341
18 -53.01967083 -75.11082100
19 -44.99863617 -53.01967083
20 -41.72518567 -44.99863617
21 -43.47978137 -41.72518567
22 -60.47276982 -43.47978137
23 -57.62001240 -60.47276982
24 -51.79530118 -57.62001240
25 -50.80231274 -51.79530118
26 -52.04771703 -50.80231274
27 -57.10380945 -52.04771703
28 -58.20197116 -57.10380945
29 -58.18794806 -58.20197116
30 -35.08277479 -58.18794806
31 -36.97058997 -35.08277479
32 -38.97058997 -36.97058997
33 -34.87943980 -38.97058997
34 -35.94254376 -34.87943980
35 -30.88645135 -35.94254376
36 -22.75323188 -30.88645135
37 -20.78828963 -22.75323188
38 -22.51483913 -20.78828963
39 -18.42368896 -22.51483913
40 -22.54989689 -18.42368896
41 -18.34656190 -22.54989689
42 4.54125328 -18.34656190
43 6.32389519 4.54125328
44 5.09952554 6.32389519
45 3.00837538 5.09952554
46 -5.18093651 3.00837538
47 2.76297108 -5.18093651
48 10.78400573 2.76297108
49 12.72090177 10.78400573
50 14.65779781 12.72090177
51 8.53158988 14.65779781
52 7.44043972 8.53158988
53 11.46848592 7.44043972
54 25.23009317 11.46848592
55 33.41239351 25.23009317
56 36.35630110 33.41239351
57 46.39837041 36.35630110
58 39.53158988 46.39837041
59 45.66480936 39.53158988
60 45.56664764 45.66480936
61 47.69285556 45.56664764
62 46.73492487 47.69285556
63 40.92423676 46.73492487
64 40.00136383 40.92423676
65 40.96630607 40.00136383
66 57.01538693 40.96630607
67 56.97331762 57.01538693
68 55.69986712 56.97331762
69 49.55963609 55.69986712
70 43.48952057 49.55963609
71 49.42641661 43.48952057
72 52.39837041 49.42641661
73 51.28618558 52.39837041
74 47.20905852 51.28618558
75 44.06882749 47.20905852
76 46.05480439 44.06882749
77 44.99871198 46.05480439
78 59.90055026 44.99871198
79 59.98468888 59.90055026
80 55.05480439 59.98468888
81 36.95664267 55.05480439
82 27.04078129 36.95664267
83 25.95664267 27.04078129
84 28.01273508 25.95664267
85 22.10388525 28.01273508
86 11.18101231 22.10388525
87 8.03376973 11.18101231
88 -0.03634578 8.03376973
89 -10.15554215 -0.03634578
90 14.93560802 -10.15554215
91 18.08986215 14.93560802
92 2.11089680 18.08986215
93 -3.72082597 2.11089680
94 -11.72783752 -3.72082597
95 -6.56657184 -11.72783752
96 -3.69277976 -6.56657184
97 -9.67875666 -3.69277976
98 -17.69979131 -9.67875666
99 -18.42634081 -17.69979131
100 -30.59461804 -18.42634081
101 -25.46841012 -30.59461804
102 -2.32817909 -25.46841012
103 -2.36323685 -2.32817909
104 -13.99863617 -2.36323685
105 -17.58495464 -13.99863617
106 -17.02403053 -17.58495464
107 -4.54023349 -17.02403053
108 5.37562790 -4.54023349
109 10.64206685 5.37562790
110 14.67011305 10.64206685
111 16.50183582 14.67011305
112 10.37562790 16.50183582
113 19.09516584 10.37562790
114 42.03907343 19.09516584
115 44.71654207 42.03907343
116 31.68849586 44.71654207
117 26.43608001 31.68849586
118 24.05745624 26.43608001
119 38.99435227 24.05745624
120 44.93124831 38.99435227
121 41.93124831 44.93124831
122 35.69285556 41.93124831
123 28.60871695 35.69285556
124 21.78400573 28.60871695
125 27.98032917 21.78400573
126 55.89619055 27.98032917
127 53.79802884 55.89619055
128 38.67883246 53.79802884
129 28.63676315 38.67883246
130 20.38434730 28.63676315
131 NA 20.38434730
> dum1 <- dum[2:length(myerror),]
> dum1
lag(myerror, k = 1) myerror
[1,] -46.09944974 -39.00829957
[2,] -58.20462301 -46.09944974
[3,] -59.16255370 -58.20462301
[4,] -67.07841509 -59.16255370
[5,] -68.16255370 -67.07841509
[6,] -46.99427647 -68.16255370
[7,] -34.98025337 -46.99427647
[8,] -48.02232268 -34.98025337
[9,] -54.91714941 -48.02232268
[10,] -64.88910320 -54.91714941
[11,] -64.91013785 -64.88910320
[12,] -57.81197613 -64.91013785
[13,] -61.69277976 -57.81197613
[14,] -68.55254873 -61.69277976
[15,] -70.15990186 -68.55254873
[16,] -72.16691341 -70.15990186
[17,] -75.11082100 -72.16691341
[18,] -53.01967083 -75.11082100
[19,] -44.99863617 -53.01967083
[20,] -41.72518567 -44.99863617
[21,] -43.47978137 -41.72518567
[22,] -60.47276982 -43.47978137
[23,] -57.62001240 -60.47276982
[24,] -51.79530118 -57.62001240
[25,] -50.80231274 -51.79530118
[26,] -52.04771703 -50.80231274
[27,] -57.10380945 -52.04771703
[28,] -58.20197116 -57.10380945
[29,] -58.18794806 -58.20197116
[30,] -35.08277479 -58.18794806
[31,] -36.97058997 -35.08277479
[32,] -38.97058997 -36.97058997
[33,] -34.87943980 -38.97058997
[34,] -35.94254376 -34.87943980
[35,] -30.88645135 -35.94254376
[36,] -22.75323188 -30.88645135
[37,] -20.78828963 -22.75323188
[38,] -22.51483913 -20.78828963
[39,] -18.42368896 -22.51483913
[40,] -22.54989689 -18.42368896
[41,] -18.34656190 -22.54989689
[42,] 4.54125328 -18.34656190
[43,] 6.32389519 4.54125328
[44,] 5.09952554 6.32389519
[45,] 3.00837538 5.09952554
[46,] -5.18093651 3.00837538
[47,] 2.76297108 -5.18093651
[48,] 10.78400573 2.76297108
[49,] 12.72090177 10.78400573
[50,] 14.65779781 12.72090177
[51,] 8.53158988 14.65779781
[52,] 7.44043972 8.53158988
[53,] 11.46848592 7.44043972
[54,] 25.23009317 11.46848592
[55,] 33.41239351 25.23009317
[56,] 36.35630110 33.41239351
[57,] 46.39837041 36.35630110
[58,] 39.53158988 46.39837041
[59,] 45.66480936 39.53158988
[60,] 45.56664764 45.66480936
[61,] 47.69285556 45.56664764
[62,] 46.73492487 47.69285556
[63,] 40.92423676 46.73492487
[64,] 40.00136383 40.92423676
[65,] 40.96630607 40.00136383
[66,] 57.01538693 40.96630607
[67,] 56.97331762 57.01538693
[68,] 55.69986712 56.97331762
[69,] 49.55963609 55.69986712
[70,] 43.48952057 49.55963609
[71,] 49.42641661 43.48952057
[72,] 52.39837041 49.42641661
[73,] 51.28618558 52.39837041
[74,] 47.20905852 51.28618558
[75,] 44.06882749 47.20905852
[76,] 46.05480439 44.06882749
[77,] 44.99871198 46.05480439
[78,] 59.90055026 44.99871198
[79,] 59.98468888 59.90055026
[80,] 55.05480439 59.98468888
[81,] 36.95664267 55.05480439
[82,] 27.04078129 36.95664267
[83,] 25.95664267 27.04078129
[84,] 28.01273508 25.95664267
[85,] 22.10388525 28.01273508
[86,] 11.18101231 22.10388525
[87,] 8.03376973 11.18101231
[88,] -0.03634578 8.03376973
[89,] -10.15554215 -0.03634578
[90,] 14.93560802 -10.15554215
[91,] 18.08986215 14.93560802
[92,] 2.11089680 18.08986215
[93,] -3.72082597 2.11089680
[94,] -11.72783752 -3.72082597
[95,] -6.56657184 -11.72783752
[96,] -3.69277976 -6.56657184
[97,] -9.67875666 -3.69277976
[98,] -17.69979131 -9.67875666
[99,] -18.42634081 -17.69979131
[100,] -30.59461804 -18.42634081
[101,] -25.46841012 -30.59461804
[102,] -2.32817909 -25.46841012
[103,] -2.36323685 -2.32817909
[104,] -13.99863617 -2.36323685
[105,] -17.58495464 -13.99863617
[106,] -17.02403053 -17.58495464
[107,] -4.54023349 -17.02403053
[108,] 5.37562790 -4.54023349
[109,] 10.64206685 5.37562790
[110,] 14.67011305 10.64206685
[111,] 16.50183582 14.67011305
[112,] 10.37562790 16.50183582
[113,] 19.09516584 10.37562790
[114,] 42.03907343 19.09516584
[115,] 44.71654207 42.03907343
[116,] 31.68849586 44.71654207
[117,] 26.43608001 31.68849586
[118,] 24.05745624 26.43608001
[119,] 38.99435227 24.05745624
[120,] 44.93124831 38.99435227
[121,] 41.93124831 44.93124831
[122,] 35.69285556 41.93124831
[123,] 28.60871695 35.69285556
[124,] 21.78400573 28.60871695
[125,] 27.98032917 21.78400573
[126,] 55.89619055 27.98032917
[127,] 53.79802884 55.89619055
[128,] 38.67883246 53.79802884
[129,] 28.63676315 38.67883246
[130,] 20.38434730 28.63676315
> z <- as.data.frame(dum1)
> z
lag(myerror, k = 1) myerror
1 -46.09944974 -39.00829957
2 -58.20462301 -46.09944974
3 -59.16255370 -58.20462301
4 -67.07841509 -59.16255370
5 -68.16255370 -67.07841509
6 -46.99427647 -68.16255370
7 -34.98025337 -46.99427647
8 -48.02232268 -34.98025337
9 -54.91714941 -48.02232268
10 -64.88910320 -54.91714941
11 -64.91013785 -64.88910320
12 -57.81197613 -64.91013785
13 -61.69277976 -57.81197613
14 -68.55254873 -61.69277976
15 -70.15990186 -68.55254873
16 -72.16691341 -70.15990186
17 -75.11082100 -72.16691341
18 -53.01967083 -75.11082100
19 -44.99863617 -53.01967083
20 -41.72518567 -44.99863617
21 -43.47978137 -41.72518567
22 -60.47276982 -43.47978137
23 -57.62001240 -60.47276982
24 -51.79530118 -57.62001240
25 -50.80231274 -51.79530118
26 -52.04771703 -50.80231274
27 -57.10380945 -52.04771703
28 -58.20197116 -57.10380945
29 -58.18794806 -58.20197116
30 -35.08277479 -58.18794806
31 -36.97058997 -35.08277479
32 -38.97058997 -36.97058997
33 -34.87943980 -38.97058997
34 -35.94254376 -34.87943980
35 -30.88645135 -35.94254376
36 -22.75323188 -30.88645135
37 -20.78828963 -22.75323188
38 -22.51483913 -20.78828963
39 -18.42368896 -22.51483913
40 -22.54989689 -18.42368896
41 -18.34656190 -22.54989689
42 4.54125328 -18.34656190
43 6.32389519 4.54125328
44 5.09952554 6.32389519
45 3.00837538 5.09952554
46 -5.18093651 3.00837538
47 2.76297108 -5.18093651
48 10.78400573 2.76297108
49 12.72090177 10.78400573
50 14.65779781 12.72090177
51 8.53158988 14.65779781
52 7.44043972 8.53158988
53 11.46848592 7.44043972
54 25.23009317 11.46848592
55 33.41239351 25.23009317
56 36.35630110 33.41239351
57 46.39837041 36.35630110
58 39.53158988 46.39837041
59 45.66480936 39.53158988
60 45.56664764 45.66480936
61 47.69285556 45.56664764
62 46.73492487 47.69285556
63 40.92423676 46.73492487
64 40.00136383 40.92423676
65 40.96630607 40.00136383
66 57.01538693 40.96630607
67 56.97331762 57.01538693
68 55.69986712 56.97331762
69 49.55963609 55.69986712
70 43.48952057 49.55963609
71 49.42641661 43.48952057
72 52.39837041 49.42641661
73 51.28618558 52.39837041
74 47.20905852 51.28618558
75 44.06882749 47.20905852
76 46.05480439 44.06882749
77 44.99871198 46.05480439
78 59.90055026 44.99871198
79 59.98468888 59.90055026
80 55.05480439 59.98468888
81 36.95664267 55.05480439
82 27.04078129 36.95664267
83 25.95664267 27.04078129
84 28.01273508 25.95664267
85 22.10388525 28.01273508
86 11.18101231 22.10388525
87 8.03376973 11.18101231
88 -0.03634578 8.03376973
89 -10.15554215 -0.03634578
90 14.93560802 -10.15554215
91 18.08986215 14.93560802
92 2.11089680 18.08986215
93 -3.72082597 2.11089680
94 -11.72783752 -3.72082597
95 -6.56657184 -11.72783752
96 -3.69277976 -6.56657184
97 -9.67875666 -3.69277976
98 -17.69979131 -9.67875666
99 -18.42634081 -17.69979131
100 -30.59461804 -18.42634081
101 -25.46841012 -30.59461804
102 -2.32817909 -25.46841012
103 -2.36323685 -2.32817909
104 -13.99863617 -2.36323685
105 -17.58495464 -13.99863617
106 -17.02403053 -17.58495464
107 -4.54023349 -17.02403053
108 5.37562790 -4.54023349
109 10.64206685 5.37562790
110 14.67011305 10.64206685
111 16.50183582 14.67011305
112 10.37562790 16.50183582
113 19.09516584 10.37562790
114 42.03907343 19.09516584
115 44.71654207 42.03907343
116 31.68849586 44.71654207
117 26.43608001 31.68849586
118 24.05745624 26.43608001
119 38.99435227 24.05745624
120 44.93124831 38.99435227
121 41.93124831 44.93124831
122 35.69285556 41.93124831
123 28.60871695 35.69285556
124 21.78400573 28.60871695
125 27.98032917 21.78400573
126 55.89619055 27.98032917
127 53.79802884 55.89619055
128 38.67883246 53.79802884
129 28.63676315 38.67883246
130 20.38434730 28.63676315
> plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
> lines(lowess(z))
> abline(lm(z))
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/70nds1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/8twcd1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
> grid()
> dev.off()
null device
1
> postscript(file="/var/www/html/rcomp/tmp/9twcd1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
> opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
> plot(mylm, las = 1, sub='Residual Diagnostics')
> par(opar)
> dev.off()
null device
1
> if (n > n25) {
+ postscript(file="/var/www/html/rcomp/tmp/10twcd1292834466.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556)
+ plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
+ grid()
+ dev.off()
+ }
null device
1
>
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/createtable")
>
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
> a<-table.row.end(a)
> myeq <- colnames(x)[1]
> myeq <- paste(myeq, '[t] = ', sep='')
> for (i in 1:k){
+ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
+ myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ')
+ if (rownames(mysum$coefficients)[i] != '(Intercept)') {
+ myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
+ if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
+ }
+ }
> myeq <- paste(myeq, ' + e[t]')
> a<-table.row.start(a)
> a<-table.element(a, myeq)
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/11efsj1292834466.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Variable',header=TRUE)
> a<-table.element(a,'Parameter',header=TRUE)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
> a<-table.element(a,'2-tail p-value',header=TRUE)
> a<-table.element(a,'1-tail p-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:k){
+ a<-table.row.start(a)
+ a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
+ a<-table.element(a,mysum$coefficients[i,1])
+ a<-table.element(a, round(mysum$coefficients[i,2],6))
+ a<-table.element(a, round(mysum$coefficients[i,3],4))
+ a<-table.element(a, round(mysum$coefficients[i,4],6))
+ a<-table.element(a, round(mysum$coefficients[i,4]/2,6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/12ixrp1292834466.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple R',1,TRUE)
> a<-table.element(a, sqrt(mysum$r.squared))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'R-squared',1,TRUE)
> a<-table.element(a, mysum$r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Adjusted R-squared',1,TRUE)
> a<-table.element(a, mysum$adj.r.squared)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (value)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[1])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
> a<-table.element(a, mysum$fstatistic[3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'p-value',1,TRUE)
> a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]))
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
> a<-table.element(a, mysum$sigma)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
> a<-table.element(a, sum(myerror*myerror))
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/13z89d1292834467.tab")
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a, 'Time or Index', 1, TRUE)
> a<-table.element(a, 'Actuals', 1, TRUE)
> a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
> a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
> a<-table.row.end(a)
> for (i in 1:n) {
+ a<-table.row.start(a)
+ a<-table.element(a,i, 1, TRUE)
+ a<-table.element(a,x[i])
+ a<-table.element(a,x[i]-mysum$resid[i])
+ a<-table.element(a,mysum$resid[i])
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/149h8g1292834467.tab")
> if (n > n25) {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'p-values',header=TRUE)
+ a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'breakpoint index',header=TRUE)
+ a<-table.element(a,'greater',header=TRUE)
+ a<-table.element(a,'2-sided',header=TRUE)
+ a<-table.element(a,'less',header=TRUE)
+ a<-table.row.end(a)
+ for (mypoint in kp3:nmkm3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mypoint,header=TRUE)
+ a<-table.element(a,gqarr[mypoint-kp3+1,1])
+ a<-table.element(a,gqarr[mypoint-kp3+1,2])
+ a<-table.element(a,gqarr[mypoint-kp3+1,3])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/15v0o41292834467.tab")
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Description',header=TRUE)
+ a<-table.element(a,'# significant tests',header=TRUE)
+ a<-table.element(a,'% significant tests',header=TRUE)
+ a<-table.element(a,'OK/NOK',header=TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'1% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant1)
+ a<-table.element(a,numsignificant1/numgqtests)
+ if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'5% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant5)
+ a<-table.element(a,numsignificant5/numgqtests)
+ if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'10% type I error level',header=TRUE)
+ a<-table.element(a,numsignificant10)
+ a<-table.element(a,numsignificant10/numgqtests)
+ if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
+ a<-table.element(a,dum)
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/www/html/rcomp/tmp/16rs4d1292834467.tab")
+ }
>
> try(system("convert tmp/1xme41292834466.ps tmp/1xme41292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xme41292834466.ps tmp/2xme41292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xme41292834466.ps tmp/3xme41292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/4pwvp1292834466.ps tmp/4pwvp1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/5pwvp1292834466.ps tmp/5pwvp1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/6pwvp1292834466.ps tmp/6pwvp1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/70nds1292834466.ps tmp/70nds1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/8twcd1292834466.ps tmp/8twcd1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/9twcd1292834466.ps tmp/9twcd1292834466.png",intern=TRUE))
character(0)
> try(system("convert tmp/10twcd1292834466.ps tmp/10twcd1292834466.png",intern=TRUE))
character(0)
>
>
> proc.time()
user system elapsed
3.493 1.742 8.505